Four time-lapse cameras, Bushnell Nature View HD Camera (Bushnell, Overland Park, KS) were installed in a soybean field to track the response of soybean plants to solar radiation, air temperature, relative humidity, soil surface temperature, and soil temperature at 5-cm depth. The purpose was to confirm if visible spectroscopy can provide useful data for tracking the condition of crops and, if so, whether game and trail time-lapse cameras can serve as reliable crop sensing and monitoring devices. Using the installed cameras, images were taken between July 22 and August 1, 2015. Color images were obtained for the daytime images captured while nighttime images were monochrome infrared (IR) images. Images at 30-minute intervals were selected for further processing and analysis, however, the nighttime images were not useful due to overexposure to the IR light which rendered the images too bright. The data from the R (red), G (green), and B (blue) bands of the images selected were extracted and exported to Microsoft Excel using the RGBExcel software application developed in-house. For each image, an AGRI (adjusted green red index) image dataset was generated based on the equation AGRI = 0.5 [1-((I_G-I_R)/(I_G+I_R))], where I_G, and I_R are the signal intensities (or pixel values) respectively in G and R bands. Next, the background (mainly soil) was removed using the Thresholding method and the remaining data averaged. This AGRI average value was plotted against the date and time of image collection, which showed a rise-and-fall trend with daily peaks around 1:00 pm. The AGRI data was regressed on logs of solar radiation, air temperature, relative humidity, soil surface temperature, and soil temperature at 5-cm depth. The following is the decreasing order of correlation: log of solar radiation (0.36 < R² < 0.65) > log of soil surface temperature (0.23 < R² < 0.38) > log of air temperature (0.09 < R² < 0.29) > log of soil temperature at 5-cm depth (0.09 < R² < 0.20) > log of relative humidity (0.00 < R² < 0.18).